Establishing the Best Methods to Measure and Improve Customer Satisfaction

Customer satisfaction is one of - if not the - most important KPIs (key performance indicators) to track in order to achieve field service business success. Ensuring the customer is happy is a priority business goal, and best-in-class service companies are almost invariably those with a keen focus on optimising the customer experience.

This is hardly surprising. As the service landscape continues to become more and more competitive, operating a customer-centric business model and consistently providing good experiences serve as powerful differentiators.

But how do you know if your customers are happy? Customer satisfaction can be gauged in a number of different ways, but truly quantifying it can be a challenge due to the fact that it is a subjective measure. Nonetheless, customer satisfaction still must be tracked in order that it may be improved.

How to Measure Customer Satisfaction

The first tactic is to conduct customer satisfaction surveys. These should be completed both at the end of a service visit, as well as during any follow-ups or billing. Customers should be asked to rank service performance based on a scale - between 1 and 5 will usually suffice - and also to provide direct feedback on how they viewed the service experience in its entirety. They should also be encouraged to voice any complaints at this point, so you know exactly where things went wrong and where any weaknesses may lie.

It's also important that you keep customer satisfaction in mind when designing your feedback collection process. The easier you make it for customers to leave feedback, the more accurate, revealing, and valuable that feedback will be. As such, you should consider how your customer satisfaction survey will display on a mobile device as well as desktop, and whether the experience of filling it out will cause any frustrations that might be reflected in the results. Consider, also, that sometimes binary Yes/No questions will suffice instead of a multi-point scale. All of this is important to get right. Good survey design will lead to honest answers, with any negative responses reflecting actual service problems that need your attention, as opposed to any irritations with the feedback collection process itself.

All feedback gathered must then be properly catalogued and evaluated. If you do get your customers to rank your service performance on a scale of 1 to 5, it will be easy to track average scores across the company, and the data can also be analysed by geography and technician. You can then use this data to inform customer satisfaction improvement programs and set goals.

Other measures that reflect customer satisfaction include contract renewals and retention rates, all of which must be tracked and analysed with the appropriate tools. Online customer review services like Yelp and comments left on social media sites such as LinkedIn, Twitter, and Facebook can also provide valuable insight into customer satisfaction levels - so these, too, must all be tracked.

Improving Customer Satisfaction - IoT and Predictive Maintenance

With systems in place to track customer satisfaction, the question is - what can you do to improve the scores you receive?

At the core, achieving good customer satisfaction rates means delivering a prompt, error-free, and exceptional service every time. Today, this increasingly means investing in technologies such as IoT (Internet of Things), machine learning, AI (artificial intelligence), and data analytics. What all these things have in common is that they have the ability to predict customers' demands, and thereby enable field service organisations to meet these demands within a very short timeframe.

With the right use of chips, sensors, and internet-connected devices, it becomes possible for companies to identify the need for services proactively - i.e. predict equipment failure before it occurs, and intervene to minimise or even eliminate business disruption. Adopting such technologies enables field service organisations to deliver customer experiences that lead to higher customer satisfaction, retention rates, and business growth.

Best-in-class service providers know that customers are most concerned about remaining operational. As such, in order to keep customer satisfaction scores high, they focus their attention on measuring the parameters - such as a device's uptime, the availability of parts, remote diagnosis of problems, and the amount of time spent on a site - that will ensure minimal disruption to the customer's operations. By tracking these parameters, service providers are able to address any problems immediately - even pre-emptively - thus preventing delays and downtime for customers, which in turn improves customer satisfaction and retention.

Another way the predictive maintenance model helps improve customer satisfaction is by helping customers save money. In the first instance, preventing costly, time-consuming equipment failures from occurring will keep the customer operational, and thereby prevent revenue loss. In addition, the data you collect from monitoring your installed equipment over time will serve to foresee what minor repairs are needed, which, if left unfixed, could translate into thousands upon thousands of Euros in replacement costs. In short, using predictive maintenance tools will help you prolong the life of your customers' equipment, minimise the amount of time spent servicing it, and reduce or eliminate the costs of replacing it.

Final Thoughts

Today, technology is driving customer satisfaction. The predictive maintenance model relies on IoT technologies, machine learning, and data analytics - all of which require investment. However, what you will be investing in is customer satisfaction. Reducing customer costs, increasing uptime, decreasing superfluous field service calls, and increasing first-time fix rates all translate into greater customer satisfaction and retention, and subsequent business growth.

Improving customer satisfaction with predictive maintenance is set to be a hot topic at Field Service Europe 2018, taking place this November at the NH Collection Amsterdam Grand Hotel Krasnapolsky, Amsterdam, Netherlands.

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